Dear R Community, I am currently student at the Vienna University of Technology writing my Diploma thesis on causality in time series and doing some analyses of time series in R. I have the following questions: (1) Is there a function in R to estimate the PARTIAL spectral coherence of a multivariate time series? If yes, how does this work? Is there an test in R if the partial spectral coherence between two variables is zero? The functions I know (spectrum, etc.) only work to estimate the spectral coherence. (2) For some causality analysis I need an estimate of the inverse of the spectral density matrix of a multivariate time series. Is there any possibility in R to get this? Actually, I would be happy if I could at least get a functional estimate of the spectral density matrix. I guess this should work because R can plot the kernel density estimator of the spectral density, so it should be possible to extract the underlying function estimate. (3) Is there any possibility to do Granger Causality in R? That means fitting an VAR model and testing if some coefficients are zero. Thank you very much in advance! Best Regards, Alexander T
Hello Alexander, for (3) see the CRAN-package "vars". Best, Bernhard> >Dear R Community, > >I am currently student at the Vienna University of Technology >writing my >Diploma thesis on causality in time series and doing some analyses of >time series in R. I have the following questions: > >(1) Is there a function in R to estimate the PARTIAL spectral >coherence >of a multivariate time series? If yes, how does this work? Is there an >test in R if the partial spectral coherence between two variables is >zero? The functions I know (spectrum, etc.) only work to estimate the >spectral coherence. > >(2) For some causality analysis I need an estimate of the >inverse of the >spectral density matrix of a multivariate time series. Is there any >possibility in R to get this? Actually, I would be happy if I could at >least get a functional estimate of the spectral density >matrix. I guess >this should work because R can plot the kernel density >estimator of the >spectral density, so it should be possible to extract the underlying >function estimate. > >(3) Is there any possibility to do Granger Causality in R? That means >fitting an VAR model and testing if some coefficients are zero. > >Thank you very much in advance! > >Best Regards, >Alexander >T > >______________________________________________ >R-help at r-project.org mailing list >https://stat.ethz.ch/mailman/listinfo/r-help >PLEASE do read the posting guide >http://www.R-project.org/posting-guide.html >and provide commented, minimal, self-contained, reproducible code. >***************************************************************** Confidentiality Note: The information contained in this message, and any attachments, may contain confidential and/or privileged material. It is intended solely for the person(s) or entity to which it is addressed. Any review, retransmission, dissemination, or taking of any action in reliance upon this information by persons or entities other than the intended recipient(s) is prohibited. If you received this in error, please contact the sender and delete the material from any computer. *****************************************************************
You can do (1) and (2) [with some additional coding] using mvspec.R, which you can download from http://www.stat.pitt.edu/stoffer/tsa2/chap7.htm ... scroll down to the Spectral Envelope section and you'll find it there. You can look at the top part of the examples to get an idea of how to use mvspec.R ... once you have the spectral matrix estimate, you can code up the extraction of the partial coherence and so on. Alexander Schnebel wrote:> > Dear R Community, > > I am currently student at the Vienna University of Technology writing my > Diploma thesis on causality in time series and doing some analyses of > time series in R. I have the following questions: > > (1) Is there a function in R to estimate the PARTIAL spectral coherence > of a multivariate time series? If yes, how does this work? Is there an > test in R if the partial spectral coherence between two variables is > zero? The functions I know (spectrum, etc.) only work to estimate the > spectral coherence. > > (2) For some causality analysis I need an estimate of the inverse of the > spectral density matrix of a multivariate time series. Is there any > possibility in R to get this? Actually, I would be happy if I could at > least get a functional estimate of the spectral density matrix. I guess > this should work because R can plot the kernel density estimator of the > spectral density, so it should be possible to extract the underlying > function estimate. > > (3) Is there any possibility to do Granger Causality in R? That means > fitting an VAR model and testing if some coefficients are zero. > > Thank you very much in advance! > > Best Regards, > Alexander > T > > ______________________________________________ > R-help at r-project.org mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide > http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. > >----- The power of accurate observation is commonly called cynicism by those who have not got it. George Bernard Shaw -- View this message in context: http://www.nabble.com/Spectral-Analysis-of-Time-Series-in-R-tp20814256p20866634.html Sent from the R help mailing list archive at Nabble.com.